Managing distributed supply-chains takes a lot of effort for planning, scheduling, monitoring, and controlling. The current study proposes and examines an approach for optimizing the transport problem inside such chains, using a decentralized approach. In this approach, models are developed for optimization of the internal operations of suppliers, logistic terminals and the transportation of components between them. The performance of these models are connected using Lagrangian relaxation, to satisfy the global objective of minimizing lateness of delivery to end users. This approach is analyzed in a case study and the simulation results are presented.
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